Optimization of the germanium preamorphization conditions forshallow-junction formation

Shallow p⁺-n and n⁺-p junctions were formed in germanium preamorphized Si substrates. Germanium implantation was carried out over the energy range of 50-125 keV and at doses from 3×10¹⁴ to 1×10¹⁵ cm^-2. p ⁺-n junctions were formed by 10-keV boron implantation at a dose of 1×10¹⁵ cm^-2. Arsenic was implanted at 50 keV at a dose of 5×10¹⁵ cm^-2 to form the n⁺-p junctions. Rapid thermal annealing was used for dopant activation and damage removal. Ge, B, and As distribution profiles were measured by secondary ion mass spectroscopy. Rutherford backscattering spectrometry was used to study the dependence of the amorphous layer formation on the energy and dose of germanium ion implantation. Cross-sectional transmission electron microscopy was used to study the residual defects formed due to preamorphization. Complete elimination of the residual end-of-range damage was achieved in samples preamorphized by 50-keV/1×10¹⁵ cm^-2 germanium implantation. Areal and peripheral leakage current densities of the junctions were studied as a function of germanium implantation parameters. The results show that high-quality p⁺-n and n⁺-p junctions can be formed in germanium preamorphized substrates if the preamorphization conditions are optimized     

Decision Based Model for Real-Time IoT Analysis Using Big Data and Machine Learning

Use of internet of things (IoT) in different fields including smart cities, health care, manufacturing, and surveillance is growing rapidly, which results in massive amount of data generated by IoT devices. Real-time processing of large-scale data streams is one of the main challenges of IoT systems. Analyzing IoT data can help in providing better services, predicting trends and timely decision making for industries. The systematic structure of IoT data follows the pattern of big data. In this paper, a novel approach is proposed in which big data tools are used to perform real-time stream processing and analysis on IoT data. We have also applied Spark’s built-in support of the machine learning library in order to make real-time predictions. The efficiency of the proposed system is evaluated by conducting experiments and reporting results on the case scenario of IoT based weather station.

     

Li–S batteries: effect of uniaxial compression on the electrical conductivity and electrochemical performance of graphene aerogel cathodes

Journal of Solid State Electrochemistry - Porous cathodes are preferred to be used in lithium-sulfur (Li–S) batteries for better impregnation of the active material. On the other hand, the...     

The self-consistent calculation of Si δ-doped GaAs structures

In this study, we report results of a self-consistent calculation obtained for the sub-band structure of Si δ-doped GaAs material by using a new alternative method. We will discuss the influence of the δ-doping concentration and the δ-layerthickness on the sub-band structure for a non-uniform distribution, which is taken as different from the known Gaussian distribution. The confining potential, the sub-band energies, the sub-band occupations, and the Fermi energy have been calculated by solving the Schr?dinger and Poisson equations by using the Airy functions self-consistently. Received: 4 December 2000 / Accepted: 31 January 2001 / Published online: 26 April 2001     

An Optimum Vertical Handoff Decision Algorithm Based on Adaptive Fuzzy Logic and Genetic Algorithm

Handoff decision making is one of the most important topics in wireless heterogeneous networks architecture as there are many parameters which have to be considered when triggering handoff and selecting suitable access point. More intelligent approaches which reckon user profiles, application requirements, and network conditions must be improved so that desired performance results for both user and network could be provided. In this paper we introduce a new adaptive vertical handoff decision making algorithm in which fuzzy membership functions are optimized by means of genetic algorithm. Genetic algorithm is an adaptive search technique based on natural selection and genetic rules. In addition to that, it takes places in various scientific applications and can be used to adjust the membership functions in fuzzy systems. The purpose of the study is to adjust the shape of fuzzy membership functions, properly, using genetic algorithm in order to achieve optimum handoff performance. The results show that, compared to the several different algorithms performance of the proposed approach with genetic algorithm is significantly improved for both user and network in terms of number of handoff while the other requirements are still satisfied.     

Selective syntheses of vinylenedithiathiophenes (VDTTs) and dithieno[2,3-b;2′,3′-d]thiophenes (DTTs); building blocks for π-conjugated systems

Selective syntheses of 3,4-vinylenedithiathiophenes (VDTTs) and dithieno[2,3-b;2′,3′-d]thiophenes (DTTs), having Ph, 4-CH₃OC₆H₄, 4-BrC₆H₄, 4-NO₂C₆H₄ and 4-(CH₃)₂NC₆H₄ groups, were achieved through the reaction of 1,8-diketone with phosphorus decasulfide (P₄S₁₀). The reaction could be shifted between VDTT and DTT by adding base (sodium bicarbonate) or acid (para-toluenesulfonic acid), respectively, to the reaction mixture. While the VDTTs were obtained in moderate yields, an important achievement has been made with the syntheses of the DTTs, obtaining them in higher yields compared with the previous report. Polymers of the VDTTs, which are the analogues of ethylenedioxythiophene, EDOT, were prepared using FeCl₃. Unfortunately, all attempts for their electropolymerization failed. Spin density calculations revealed that none of the VDTTs had a significant positive spin density at the ‘α’ carbon atoms of the thiophene ring. Considering their solubility and functional groups, which could be further derivatized, they are useful building blocks for the preparation of new organic materials.     

MOCVD growth and optical properties of non-polar (1 1–2 0) a-plane GaN on (1 0–1 2) r-plane sapphire substrate

Non-polar a-plane GaN film with crystalline quality and anisotropy improvement is grown by use of high temperature AlN/AlGaN buffer, which is directly deposited on r-plane sapphire by pulse flows. Compared to the a-plane GaN grown on AlN buffer, X-ray rocking curve analysis reveals a remarkable reduction in the full width at half maximum, both on-axis and off-axis. Atomic force microscopy image exhibits a fully coalesced pit-free surface morphology with low root-mean-square roughness (∼1.5 nm). Photoluminescence is carried out on the a-plane GaN grown on r-plane sapphire. It is found that, at low temperature, the dominant emission at ∼3.42 eV is composed of two separate peaks with different characteristics, which provide explanations for the controversial attributions of this peak in previous studies.     

Facile syntheses of 3-hydroxyflavones

Modification of the present synthetic methods led to the syntheses of 3-hydroxyflavones in a shorter reaction time, with simple purification and higher yields. Application of the method provided the syntheses of 3HFs having a hydroxyl group on the phenyl ring (ring B) in one step, which is an improvement compared to the four steps, long reaction time, and low yield using the current method available in the literature.